Rock and its properties can be determined with the help of images data. Photographs can be a good assist in rock mass classification, first by allowing zones with different patterns to be identified and the boundaries between them defined and secondly by allowing the distribution of block sizes and shapes.
In the last decade, the industry has developed methods for characterizing carbonate rocks at microscopic scale using Confocal microscopy, Micro-/Nano-X-ray Computed Tomography (CT), Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) or at macroscopic scales using CT scan technology and ordinary microscopy methods. These methodologies allow studying digital data and analyzing the distribution of the pore network in three dimensions, in order to determine petrophysical properties. Great emphasis has been placed on these techniques to determine the storage capability and flow of rock cores. However, it is needless to say that such capabilities are affected by components constituting the rock and that the distribution of the components affects the petrophysical properties.
Density appears to be an easy concept to understand. At its most basic definition, it is a very simple and straight forward concept. Simply divide the mass of an object by the volume. However, when it comes time to start adding in additional factors like porosity, permeability, absorption rates, pore sizes, and the processes that form the samples themselves things can easily become complicated. Most things in the geotechnical engineering world do not fall in perfect geometric shapes, so the ability to accurately assess the volume of a sample is vital.
Traditional methods for estimating size and porous distributions are indirect therefore they can be inaccurate carrying out measurement errors. Measurements from photographs or formation microimager have relied on counting only the wholly visible fragments, ignoring the ones overlapped by other particles, giving a serious sampling bias.
Hydraulic conductivity of the rock mass depends on spacing and connectivity of the network of joints, and on the roughness and apertures of each individual joint. To understand the fluid behavior and the rock interactions, the evolution of physical and morphological characteristics of connected space and the rock walls have to be modelled.
In situ rocks need to be viewed from several directions to adequate sample a 3D pattern. The CT scan provides a measurement of the attenuation of the radiation of the X-ray in certain volume or the whole volume of a plug sample of rock. The CT scan provides a 3D representation of the scanned object wherein said representation is a 3D image described by voxels.
A voxel represents a value on a regular grid in three-dimensional space wherein said voxel is often represented by a parallelepiped. The set of voxels of the 3D image are a discretization of the volume that has been scanned and the color value of the image may represent a scalar function defined in said discretization. CT scan, as it will be used along this description, provides a gray scale and the gray value represents the value (scalar value) of the measurement of the attenuation of the radiation in a range. The gray value will be used as a measurement, a measurement of the attenuation of the radiation of the X-ray, taken from the sample at each point of the discretization defined by the 3D image.
The CT scan does not provide absolute values of physical properties such as the density, just gray values that may be qualitatively assessed by an expert. These 3D images are very useful for the understanding of the structure of the sample of rock scanned but, even if the measurement of the attenuation of the radiation is proportional to the density, the image is not a measurement of the density. For instance, when a CT scan scans twice the same sample of rock, the second measurement differs from the first one due to the CT scan works under different conditions and the gray values cannot be interpreted as absolute measurements of the density.
Because the above identified limitations, physical properties such as density, porosity and permeability, cannot be characterized by CT scan techniques.
The discretization of the 3D image provided by a CT scan is not a numerical model of a sample of rock as it lacks of the structural properties reproducing the behavior of the sample of rock.
The measurements of porosity may be carried out in a lab for instance to obtain the total porosity of the sample of rock. The same applies to the measurement of the permeability wherein the permeability is measured by forcing a flow across the sample of rock in a predetermined direction and under certain conditions. These measurements highly depend on the internal structure and properties of the rock but they do not provide data to allow disclosing the internal structure of the sample of rock.
For instance, the fluid may easily flow because the high permeability of the whole sample of rock or because, even if the permeability of the whole sample of rock is low, the existence of a fracture defines a path for the flow with a very low resistance to the flow. A numerical model must comprise an internal structure providing the same flow behavior than the physical sample of rock.
The internal structure of a rock can be divided by facies. Each facies is determined by the same spatial relation and internal characteristic such as lithology and sedimentary structures.
Numerical simulations of reservoirs need characterizing properties of facies mainly according to the porosity and permeability properties in order to be able to simulate the behavior in the entire domain. The proposed numerical model determines the physical properties, including porosity and permeability, of a sample of rock from an oil or gas reservoir. The sample of rock, called plug sample, is extracted and analyzed from a vertical or horizontal portion of the core. The core is a sample of the reservoir formation extracted from a well according to its longitudinal direction.
If an oil or gas reservoir comprises a plurality of facies, at least one sample of rock is taken for each facies. According to a first aspect of the invention, a numerical model for each facies allows to model separately each facies. According to an embodiment of the present invention, the plurality of numerical models are used for generating a further numerical model of a core comprising a plurality of facies, being said core extracted from a well.
The problem solved by the invention is a numerical model that determines the physical properties of the sample of rock such that, when the numerical model is used to populate the properties in a certain domain, for instance in a facies or in the complete sample extracted from the well, the flow behavior of the numerical model or the flow behavior of the populated domain are according to the measurements taken from the sample of rock.